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Design and build data pipelines, warehouses, and lakes for enterprise clients, using SQL, Python, and cloud platforms like Snowflake.
Lead AI initiatives for banking clients, designing GenAI chatbots and automation workflows using Microsoft AI tools and LLMs, while mentoring teams and aligning AI projects with business goals.
Build and maintain Java-based enterprise systems and design automated testing frameworks using Spring, JUnit, and CI/CD tools.
Build and optimize cloud-native data pipelines on Azure, migrating and transforming data for analytics and ML workloads using Spark, Databricks, and Azure Synapse.
Build and maintain scalable Azure Databricks data pipelines and analytics for HR tech, using Spark, SQL and Azure services to automate employee lifecycle data flows.
Maintains and optimizes Talend ETL/ELT pipelines to ensure reliable data integration and high-quality enterprise data flows.
Build and maintain Talend ETL/ELT pipelines, troubleshoot issues, and ensure reliable data integration for enterprise systems in Jeddah.
Build and maintain data quality frameworks and pipelines, enforcing standards across systems and mentoring teams to ensure reliable enterprise data.
Maintain and optimize Talend ETL/ELT pipelines to ensure reliable data integration for PVH’s production systems in Jeddah.
Design and maintain data quality frameworks, rules, and automated checks to ensure enterprise data accuracy and reliability across systems.
Maintains and optimizes Talend ETL/ELT pipelines for a 4-month on-site project, ensuring reliable data integration and resolving pipeline issues.
Designs and maintains scalable data pipelines, warehouses, and governance frameworks using Python, SQL, and cloud tools to ensure clean, reliable data for analytics and reporting.
Build and maintain cloud-based data pipelines and warehouses for clients using AWS, SQL, and ETL tools like SnapLogic or Informatica.
Designs and builds data pipelines and warehouses using ETL tools, SQL/NoSQL databases, and big-data platforms to ensure clean, reliable data for analytics and business decisions.
Senior Data Engineer builds and operates scalable cloud/on-prem data architectures, pipelines, and models to store, integrate, and secure enterprise data assets for AI and analytics workloads.
Lead hands-on ETL and data-migration projects, designing pipelines, writing SQL/Python, and guiding clients through legacy-to-target migrations until go-live.
Builds and maintains automated data pipelines using Spark, Kafka, Airflow, and cloud platforms like Azure or AWS to integrate and process large-scale data for AI-driven analytics.
Designs and maintains scalable data pipelines and warehouses (e.g., Fabric, Databricks) to collect, store, and analyze data for analytics and ML, using SQL, Python, and cloud platforms.
Designs and maintains scalable data pipelines and ETL processes using SQL, Python, and cloud tools to support analytics and decision-making.
Designs and maintains data pipelines and systems using SQL, Spark, Python, and Azure tools to process and analyze raw data for business insights.
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